Iron-Epoxy composite samples were prepared by added
different weight percentages (0, 5, 10, 15, and 20 wt %) from Iron
particles in the range of (30-40μm) as a particle size. The contents
were mixed carefully, and placed a circular dies with a diameter of
2.5 cm. Different mechanical tests (Shore D Hardness, Tensile
strength, and Impact strength ) were carried out for all samples. The
samples were immersed in water for ten weeks, and after two weeks
the samples were take-out and drying to conducting all mechanical
tests were repeated for all samples. The hardness values increased
when the Iron particle concentration increased while the Impact
strength is not affected by the increasing of Iron particles
c

Lipopolysaccharide (LPS) of Campylobacter coli was extracted using digestive enzyme and hot phenol water method. Anti-LPS was prepared by injecting rabbits with different concentration of LPS. The result showed that the titer of anti-LPS antibodies using precipitation test is 40, the result also showed Histopathological effect of partial pure LPS. It was found that the LPS caused slightly effect represent as intestinal villi atrophy and aggregation of hyperplasia of lymphocyte cells payers patch, while effect on liver was sinusoids dilation with few inflammation cell infiltration, congestion and dispersed necrotized hepatocyte. Also we found effects on spleen cell as widening of white and red pulp, diffused hyperplasia of lymphoid cells and

Background: Exposure to microwaves radiation from microwave oven may be harmful for users especially for the one who have highest contact with microwave oven. Because the body is electrochemical in nature, any force that disrupts or changes human electrochemical events will affect the physiology of the body by destabilization and interruption of many chemical body substance including growth factors.The insulin-like growth factors (IGFs) are a family of mitogenic proteins that control growth, differentiation, and the maintenance of differentiated function in numerous tissues. It fulfils an important role in growth and development of teeth, mandible, maxillae, and tongue. Platelet derived growth factors (PDGF) are proteins that regulate cell

In this work, ZnO nanostructures for powder ZnO were synthesized by Hydrothermal Method. Size and shape of ZnO nanostructureas can be controlled by change ammonia concentration. In the preparation of ZnO nanostructure, zinc nitrate hexahydrate [Zn(NO₃)₂·6H2O] was used as a precursor. The structure and morphology of ZnO nanostructure have been characterized by scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray diffraction (XRD). The synthesized ZnO nanostructures have a hexagonal wurtzite structure. Also using Zeta potential and Particle Size Analyzers and size distribution of the ZnO powder

Thermal conductivity of compacted bentonite is one of the most important properties where this type of clay is proposed for use as a buffer material. In this study, Lee's disc method was used to measure the thermal conductivity of compacted bentonite specimens. The experimental results have been analyzed to observe the three major factors affecting the thermal conductivity of bentonite buffer material. While the clay density reaches to a target value, the measurement is taken to evaluate the thermal conductivity. By repeating this procedure, a relationship between clay dry density and thermal conductivity has been established in specimens after adjusting the water contents of the bentonite by placing its specimens in a drying oven for diffe

Sixty samples of commercially available contact lens solutions were collected from students at the Pharmacy College/Baghdad University. The types of lenses used varied from medical to cosmetic. They were cultured to diagnose any microbial contamination within the solutions. Both used and unused solutions were subject for culturing. Thirty six (60%) used samples showed bacterial growth, fungal growth was absent. Pseudomonas aeruginosa accounts for the highest number of isolates (25%) followed by E. coli (21%), Staphylococcus epidermidis (6.6%), Pseudomonas fluorescence (5%) and Proteus mirabilis (1.6%) respectively. Only one (1) unused (sealed) sample showed growth of P. fluorescence.

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a